PayQL
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct purpose: preflight cost estimation, schema introspection, actual query execution, subgraph search, and wallet status. No overlap or ambiguity.
Naming Consistency4/5Most tools follow a clear verb_noun pattern (get_payment_info, get_subgraph_schema, query_subgraph, search_subgraphs). wallet_status deviates slightly but remains clear and consistent in style.
Tool Count5/5Five tools cover the essential operations for a payment-based subgraph query service: preflight, schema, query, search, and wallet management. The count is well-scoped without unnecessary tools.
Completeness4/5The tool set covers the core workflow: discovery, schema exploration, cost estimation, querying, and wallet status. A minor gap is the lack of a direct funding tool, but the query tool handles insufficient balance by returning funding instructions.
Average 4.2/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 29 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It explicitly states key behavioral traits: preflight action without payment ('WITHOUT paying'). No contradictions, but could mention side effects or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, well-structured sentence. It front-loads the action and lists return fields efficiently with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description lists return fields (USDC price, asset, payTo, network). It covers the primary behavior and inputs but could describe output structure or error scenarios more fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both parameters have descriptions), so baseline is 3. The tool description does not add extra parameter semantics beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: 'Preflight a subgraph' to 'return the USDC price, asset, payTo and network' without payment. It uses specific verbs and specifies the resource, differentiating it from sibling tools like query_subgraph and search_subgraphs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides clear usage context: 'Use to estimate cost or to drive a harness-side payment.' It implies when to use but does not explicitly state when not to use or compare with alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the query is paid (x402) and reactive, indicating no side effects since it's a read-only introspection. It does not mention rate limits or data volume, but the scope is limited to root entities.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, with no redundant wording. The first sentence states the core action and paid nature, and the second sentence gives usage guidance. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a single parameter, no output schema, and no annotations, the description covers the necessary context: what it does, when to use it, and the cost implication. It could briefly mention the output format (GraphQL schema) but is sufficiently complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The sole parameter 'subgraph_id' is described in the schema as 'Subgraph ID', and the description adds no additional meaning or format guidance. The description does not explain how to obtain or format the ID.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists a subgraph's root queryable entities via GraphQL introspection, with a specific verb ('list') and resource ('subgraph's root queryable entities'). It distinguishes from sibling tools like query_subgraph (which executes queries) and search_subgraphs (searching), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description advises using the tool 'before composing a real query', indicating the appropriate context. It mentions it's a 'paid x402 query', alerting users to cost. However, it does not explicitly state when not to use it or provide alternative tools for similar tasks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses payment via x402, returns data plus receipt, respects spend cap, and returns fund-wallet message on insufficient balance. This is good transparency for a paid tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action and key details. No redundancy or waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description covers return values (data plus payment receipt). It provides enough context for an agent to understand the tool's role among siblings. Could be slightly improved by noting that the receipt includes tx hash and amount.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds payment context but does not elaborate on parameter usage beyond what the schema provides. The subgraph_id description references search_subgraphs, which is helpful.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool runs a GraphQL query against a subgraph on The Graph with payment. It distinguishes itself from siblings like search_subgraphs and get_subgraph_schema by specifying the action (query vs search/schema) and the payment mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (for paid queries against subgraphs) and mentions conditions like spend cap and balance insufficient behavior. However, it does not explicitly contrast with sibling tools or state when not to use it, e.g., for schema retrieval use get_subgraph_schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states that the tool never reveals the private key, addressing a critical security concern. Since no annotations are present, this behavioral disclosure is valuable. However, it does not explicitly state that the tool is read-only or idempotent, which would further improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads all key information: the reported items and the security guarantee. Every phrase adds value, with no redundancy or vague language. It is optimally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of parameters and output schema, the description provides a complete picture of the tool's output. It covers all relevant details (payment mode, wallet address, balances, spend cap, funding instructions) and the security constraint. No additional context is needed for an agent to understand its use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, and the description provides full coverage of what the tool returns. This adds meaning beyond the empty schema by listing the exact fields reported. The baseline for zero parameters is 4, and the description's list of fields justifies a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reports specific wallet and payment status information: payment mode, wallet address, USDC/ETH balance, spend cap, and funding instructions. The verb 'report' and the listed items precisely define the tool's functionality, distinguishing it from sibling tools like 'get_payment_info' which may focus on payment info only.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not advise when to use this tool over siblings such as 'get_payment_info', nor does it mention prerequisites or context. The agent receives no guidance on when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses default behavior (tiny PAID x402 query) and config alternative (PAYQL_REGISTRY_URL for free source). No annotations exist, so description carries the burden well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences: first defines purpose, second adds critical usage context. No fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema; description mentions ranking but not specific return fields. For a search tool, more detail on result structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage 100%, description adds meaning like 'ranked by on-chain curation signal' and default for 'first'. Adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'find' and resource 'live subgraphs', mentions ranking by curation signal, and distinguishes from siblings like query_subgraph.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
States 'Use this to pick a subgraph_id before querying', providing clear context. Does not explicitly list when not to use or compare to siblings, but implication is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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